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Classification and Prediction of VOCs Using an IoT-Enabled Electronic Nose System-Based Lab Prototype for Breath Sensing Applications.
ACS Sens
January 2025
Interdisciplinary Research Division Smart HealthCare, Indian Institute of Technology Jodhpur, Jodhpur 342030, India.
Electronic nose (e-nose) systems are well known in breath analysis because they combine breath printing with advanced and intelligent machine learning (ML) algorithms. This work demonstrates development of an e-nose system comprising gas sensors exposed to six different volatile organic compounds (VOCs). The change in the voltage of the sensors was recorded and analyzed through ML algorithms to achieve selectivity and predict the VOCs.
View Article and Find Full Text PDFA remote monitoring approach for coastal engineering projects.
Sci Rep
January 2025
School Geography & Environmental Sciences, Ulster University, Coleraine, UK.
High costs and project-based (short-term) financing mean that coastal engineering projects are often undertaken in the absence of appropriate post-construction monitoring programmes. Consequently, the performance of shoreline-stabilizing structures or beach nourishments cannot be properly quantified. Given the high value of beaches and the increase in erosion problems and coastal engineering responses, managers require as much accurate data as possible to support efficient decision-making.
View Article and Find Full Text PDFRetinal vasculature changes as indicators of imaging signs of cerebral small vessel disease: A community-based, cross-sectional study of older adults.
J Clin Neurosci
January 2025
Department of Neurology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China; Hubei Key Laboratory of Neural Injury and Functional Reconstruction, Huazhong University of Science and Technology, China. Electronic address:
Objectives: This study investigated the correlation between retinal vasculature and cerebral small vessel disease (CSVD) imaging markers, providing new evidence for the retina-brain association.
Methods: Two hundred and thirty-nine participants aged 55-85 were enrolled in the study. CSVD indicators, encompassing white matter hyperintensities (WMHs), lacunes (LAs), cerebral microbleeds (CMBs), and enlarged perivascular spaces (EPVSs), were assessed.
Plug-and-play myoelectric control via a self-calibrating random forest common model.
J Neural Eng
January 2025
School of Informatics, The University of Edinburgh, 10 Chricton Street, Edinburgh, EH8 9LE, UNITED KINGDOM OF GREAT BRITAIN AND NORTHERN IRELAND.
Objective: Electromyographic (EMG) signals show large variabilities over time due to factors such as electrode shifting, user behaviour variations, etc., substantially degrading the performance of myoelectric control models in long-term use. Previously one-time model calibration was usually required each time before usage.
View Article and Find Full Text PDFDeep Learning Enabled Scoring of Pancreatic Neuroendocrine Tumors Based on Cancer Infiltration Patterns.
Endocr Pathol
January 2025
Department of Computer Engineering, Koc University, Istanbul, Turkey.
Pancreatic neuroendocrine tumors (PanNETs) are a heterogeneous group of neoplasms that include tumors with different histomorphologic characteristics that can be correlated to sub-categories with different prognoses. In addition to the WHO grading scheme based on tumor proliferative activity, a new parameter based on the scoring of infiltration patterns at the interface of tumor and non-neoplastic parenchyma (tumor-NNP interface) has recently been proposed for PanNET categorization. Despite the known correlations, these categorizations can still be problematic due to the need for human judgment, which may involve intra- and inter-observer variability.
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